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Evaluation of Detecting Malicious Nodes Using Bayesian Model in Wireless Intrusion Detection

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Network and System Security (NSS 2013)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7873))

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Abstract

Wireless sensor network (WSN) is vulnerable to a wide range of attacks due to its natural environment and inherent unreliable transmission. To protect its security, intrusion detection systems (IDSs) have been widely deployed in such a wireless environment. In addition, trust-based mechanism is a promising method in detecting insider attacks (e.g., malicious nodes) in a WSN. In this paper, we thus attempt to develop a trust-based intrusion detection mechanism by means of Bayesian model and evaluate it in the aspect of detecting malicious nodes in a WSN. This Bayesian model enables a hierarchical wireless sensor network to establish a map of trust values among different sensor nodes. The hierarchical structure can reduce network traffic caused by node-to-node communications. To evaluate the performance of the trust-based mechanism, we analyze the impact of a fixed and a dynamic trust threshold on identifying malicious nodes respectively and further conduct an evaluation in a wireless sensor environment. The experimental results indicate that the Bayesian model is encouraging in detecting malicious sensor nodes, and that the trust threshold in a wireless sensor network is more dynamic than that in a wired network.

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Author information

Authors and Affiliations

  1. Department of Computer Science, College of Science and Engineering, City University of Hong Kong, Hong Kong, China

    Yuxin Meng & Lam-for Kwok

  2. Computer Science Division, Zhaoqing Foreign Language College, Guangdong, China

    Wenjuan Li

Authors
  1. Yuxin Meng
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  2. Wenjuan Li
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  3. Lam-for Kwok
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Editor information

Editors and Affiliations

  1. Computer Science Department, ETSI Informatica, University of Malaga, Campus de Teatinos, 29071, Malaga, Spain

    Javier Lopez

  2. School of Mathematics and Computer Science, Fujian Normal University, No. 32 Shangsan Road, 350007, Fuzhou, China

    Xinyi Huang

  3. Institute for Cyber Security,, University of Texas at San Antonio, One UTSA Circle, 78249, San Antonio, TX, USA

    Ravi Sandhu

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© 2013 Springer-Verlag Berlin Heidelberg

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Meng, Y., Li, W., Kwok, Lf. (2013). Evaluation of Detecting Malicious Nodes Using Bayesian Model in Wireless Intrusion Detection. In: Lopez, J., Huang, X., Sandhu, R. (eds) Network and System Security. NSS 2013. Lecture Notes in Computer Science, vol 7873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38631-2_4

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  • DOI: https://doi.org/10.1007/978-3-642-38631-2_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38630-5

  • Online ISBN: 978-3-642-38631-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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